Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power

Journal of Cardiovascular Magnetic Resonance

Research

Niall G Keenan¹  Wenzhe Shi²  Daniel Rueckert²  Giovanni Montana³  Christopher Minas³  Timothy JW Dawes⁴  Giuliana Durighel⁴  Antonio de Marvao⁴  Tamara Diamond⁴  Declan P O’Regan⁴  Stuart A Cook⁵ 

[1] Department of Cardiology, Imperial College NHS Healthcare Trust, Du Cane Road, W12 0HS, London, UK;Department of Computing, Imperial College London, Kensington Campus, Exhibition Road, SW7 2AZ, London, UK;Department of Mathematics, Imperial College London, South Kensington Campus, Exhibition Road, SW7 2AZ, London, UK;From the Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, W12 0NN, London, UK;From the Medical Research Council Clinical Sciences Centre, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, Du Cane Road, W12 0NN, London, UK;Department of Cardiology, National Heart Centre Singapore, 17 Third Hospital Ave, 168752, Singapore, Singapore;Duke-NUS, 8 College Road, 169857, Singapore, Singapore;

关键词: Imaging-genetics;    LVH;    Cardiomyopathy;    GWAS;    Biobank;    Cardiovascular magnetic resonance;    Image analysis;   

DOI  :  10.1186/1532-429X-16-16

 received in 2013-10-28, accepted in 2014-01-29,  发布年份 2014

来源: Springer

【 摘 要 】

BackgroundCardiac phenotypes, such as left ventricular (LV) mass, demonstrate high heritability although most genes associated with these complex traits remain unidentified. Genome-wide association studies (GWAS) have relied on conventional 2D cardiovascular magnetic resonance (CMR) as the gold-standard for phenotyping. However this technique is insensitive to the regional variations in wall thickness which are often associated with left ventricular hypertrophy and require large cohorts to reach significance. Here we test whether automated cardiac phenotyping using high spatial resolution CMR atlases can achieve improved precision for mapping wall thickness in healthy populations and whether smaller sample sizes are required compared to conventional methods.MethodsLV short-axis cine images were acquired in 138 healthy volunteers using standard 2D imaging and 3D high spatial resolution CMR. A multi-atlas technique was used to segment and co-register each image. The agreement between methods for end-diastolic volume and mass was made using Bland-Altman analysis in 20 subjects. The 3D and 2D segmentations of the LV were compared to manual labeling by the proportion of concordant voxels (Dice coefficient) and the distances separating corresponding points. Parametric and nonparametric data were analysed with paired t-tests and Wilcoxon signed-rank test respectively. Voxelwise power calculations used the interstudy variances of wall thickness.ResultsThe 3D volumetric measurements showed no bias compared to 2D imaging. The segmented 3D images were more accurate than 2D images for defining the epicardium (Dice: 0.95 vs 0.93, P < 0.001; mean error 1.3 mm vs 2.2 mm, P < 0.001) and endocardium (Dice 0.95 vs 0.93, P < 0.001; mean error 1.1 mm vs 2.0 mm, P < 0.001). The 3D technique resulted in significant differences in wall thickness assessment at the base, septum and apex of the LV compared to 2D (P < 0.001). Fewer subjects were required for 3D imaging to detect a 1 mm difference in wall thickness (72 vs 56, P < 0.001).ConclusionsHigh spatial resolution CMR with automated phenotyping provides greater power for mapping wall thickness than conventional 2D imaging and enables a reduction in the sample size required for studies of environmental and genetic determinants of LV wall thickness.

【 授权许可】

CC BY   
© de Marvao et al.; licensee BioMed Central Ltd. 2014